While recent Transformer-based approaches have shown impressive performances on
event-based object detection tasks their high computational costs still diminish the low …

While transformers have greatly boosted performance in semantic segmentation, domain
adaptive transformers are not yet well explored. We identify that the domain gap can cause …

With the increasing application of embedded mobile devices in various fields, lightweight
real-time semantic segmentation systems have attracted more and more attention. Many …

Affordance grounding aims to localize the interaction regions for the manipulated objects in
the scene image according to given instructions, which is essential for Embodied AI and …

Normalization techniques are crucial for enhancing Transformer models' performance and
stability in time series analysis tasks, yet traditional methods like batch and layer …

Indirect forms of language, such as sarcasm, are highly prevalent in contemporary human
daily communication. While the indirect nature of metaphorical language ensures that …

Traffic prediction is a vital aspect of Intelligent Transportation Systems with widespread
applications. The main challenge is accurately modeling the complex spatial and temporal …

Cracks are a prevalent disease on pavement concrete materials. Timely assessment and
repair of concrete materials can significantly extend their service life. However, accurate …

Referring Expression Segmentation (RES) has attracted rising attention, aiming to identify
and segment objects based on natural language expressions. While substantial progress …

The coordinated utilization of diverse types of satellite sensors provides a more
comprehensive view of the Earth's surface. However, due to the significant heterogeneity …